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PaddleSpeech/data/aishell/aishell.py

110 lines
3.7 KiB

"""Prepare Aishell mandarin dataset
Download, unpack and create manifest files.
Manifest file is a json-format file with each line containing the
meta data (i.e. audio filepath, transcript and audio duration)
of each audio file in the data set.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import codecs
import soundfile
import json
import argparse
from data_utils.utility import download, unpack
DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset/speech')
URL_ROOT = 'http://www.openslr.org/resources/33'
DATA_URL = URL_ROOT + '/data_aishell.tgz'
MD5_DATA = '2f494334227864a8a8fec932999db9d8'
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument(
"--target_dir",
default=DATA_HOME + "/Aishell",
type=str,
help="Directory to save the dataset. (default: %(default)s)")
parser.add_argument(
"--manifest_prefix",
default="manifest",
type=str,
help="Filepath prefix for output manifests. (default: %(default)s)")
args = parser.parse_args()
def create_manifest(data_dir, manifest_path_prefix):
print("Creating manifest %s ..." % manifest_path_prefix)
json_lines = []
transcript_path = os.path.join(data_dir, 'transcript',
'aishell_transcript_v0.8.txt')
transcript_dict = {}
for line in codecs.open(transcript_path, 'r', 'utf-8'):
line = line.strip()
if line == '': continue
audio_id, text = line.split(' ', 1)
# remove withespace
text = ''.join(text.split())
transcript_dict[audio_id] = text
data_types = ['train', 'dev', 'test']
for type in data_types:
audio_dir = os.path.join(data_dir, 'wav', type)
for subfolder, _, filelist in sorted(os.walk(audio_dir)):
for fname in filelist:
audio_path = os.path.join(subfolder, fname)
audio_id = fname[:-4]
# if no transcription for audio then skipped
if audio_id not in transcript_dict:
continue
audio_data, samplerate = soundfile.read(audio_path)
duration = float(len(audio_data) / samplerate)
text = transcript_dict[audio_id]
json_lines.append(
json.dumps(
{
'audio_filepath': audio_path,
'duration': duration,
'text': text
},
ensure_ascii=False))
manifest_path = manifest_path_prefix + '.' + type
with codecs.open(manifest_path, 'w', 'utf-8') as fout:
for line in json_lines:
fout.write(line + '\n')
def prepare_dataset(url, md5sum, target_dir, manifest_path):
"""Download, unpack and create manifest file."""
data_dir = os.path.join(target_dir, 'data_aishell')
if not os.path.exists(data_dir):
filepath = download(url, md5sum, target_dir)
unpack(filepath, target_dir)
# unpack all audio tar files
audio_dir = os.path.join(data_dir, 'wav')
for subfolder, _, filelist in sorted(os.walk(audio_dir)):
for ftar in filelist:
unpack(os.path.join(subfolder, ftar), subfolder, True)
else:
print("Skip downloading and unpacking. Data already exists in %s." %
target_dir)
create_manifest(data_dir, manifest_path)
def main():
if args.target_dir.startswith('~'):
args.target_dir = os.path.expanduser(args.target_dir)
prepare_dataset(
url=DATA_URL,
md5sum=MD5_DATA,
target_dir=args.target_dir,
manifest_path=args.manifest_prefix)
if __name__ == '__main__':
main()